Nearly all adaptive optics (AO) systems for the human eye use a wavefront sensor-driven correction. Wavefront sensorless AO offers several potential benefits, such as enhanced aberration correction due to the elimination of non-common path errors and wavefront sensor noise. Sensorless AO has been demonstrated by Biss et al. [1] to image the mouse retina in vivo and by Zommer et al. [2] in a human eye with a double-pass point image. We have implemented a wavefront sensorless AO control method in a confocal adaptive optics scanning laser ophthalmoscope (AOSLO) and demonstrated its feasibility in an artificial and living human eye. A stochastic parallel gradient descent (SPGD) algorithm was used to directly optimize the 140 dimensional actuator space of a MEMS deformable mirror to maximize the average light intensity in the AOSLO retinal image. We simulated the SPGD AO method for correcting the wave aberration and compared it to real-time performance. Currently, our wavefront sensor-driven control method converges faster than our sensorless AO control method. However, image quality in a static, artificial eye and an undilated human eye following sensorless AO correction rivaled that of a wavefront sensor-based correction in the same system. Future optimization of this technique could provide faster, improved corrections using less incident light than wavefront sensor based-methods, which may be particularly beneficial for psychophysics and autofluorescence imaging. Wavefront sensorless correction could also yield cheaper, simpler AO systems and potentially image individuals who are difficult to correct using wavefront sensors.

Acknowledgments

Research supported by grants from NIH (EY019069 and P30 EY007551) and the Texas Advanced Research Program (G096152).